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Pathway Volcano: an interactive tool for pathway guided visualization of differential expression data

  • 0Department of Otolaryngology, Head & Neck Surgery, Indiana University School of Medicine, Indianapolis, IN 46202, United States.
Bioinformatics +

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June 28, 2025

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June 28, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Omics data visualization is challenging. Pathway Volcano, an R-Shiny tool, simplifies interpretation by filtering volcano plots for specific biological pathways, revealing hidden significant features.

Area Of Science

  • Bioinformatics
  • Computational Biology
  • Data Visualization

Background

  • Omics datasets (e.g., RNA-sequencing, proteomics) are large and complex, posing visualization challenges.
  • Standard volcano plots struggle to display thousands of significant features, leading to data overlap and reduced interpretability.
  • Effective visualization is crucial for understanding differential expression in biological research.

Purpose Of The Study

  • To develop a novel tool, Pathway Volcano, for simplifying the visualization and interpretation of large omics datasets.
  • To enhance the biological insight derived from differential expression analysis by focusing on specific pathways.
  • To address the limitations of traditional volcano plots in handling complex omics data.

Main Methods

  • Developed Pathway Volcano as a freely available R Shiny package.
  • Utilized the Reactome API to select and filter data by specific biological pathways.
  • Implemented interactive features for data interrogation and visualization.

Main Results

  • Pathway Volcano effectively filters volcano plots to display data associated with selected pathways.
  • The tool reveals significant features often obscured in crowded regions of standard volcano plots.
  • Interactive features allow for detailed data exploration and pathway impact assessment.

Conclusions

  • Pathway Volcano offers a biologically informative approach to simplify omics data visualization and interpretation.
  • The tool enhances the ability to identify and understand the impact of specific pathways in differential expression studies.
  • This software provides a valuable resource for researchers working with complex omics datasets.